import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

tips = sns.load_dataset("tips",cache=True, data_home='.')
sns.set_style('whitegrid')
#sns.set_palette('Blues')

g = sns.lmplot(x='tip', y='total_bill', data=tips, aspect=2)
g = g.set_axis_labels("Total Bill", "Tip").set(xlim=(0, 10), ylim=(0, 100))
plt.title('title')
plt.savefig('example_07_01.png')
plt.cla()

from sklearn import datasets
diab = datasets.load_iris()
x1 = [item[0] for item in  diab.data]
print(x1)
sns.distplot(a=x1,kde=True)
plt.savefig('example_07_02.png')

plt.cla()

sns.displot(data=x1,kind='ecdf')
plt.savefig('example_07_03.png')

plt.cla()

sns.boxplot(x=diab.target,y=x1)
plt.savefig('example_07_04.png')

plt.cla()

sns.pairplot(data=pd.DataFrame(diab.data,columns=diab.feature_names), diag_kind='kde')
plt.savefig('example_07_05.png')